A variety of data mining systems and methods are known for detecting associations among items stored or represented in a database. For example, in the context of an electronic catalog of items, data mining processes are frequently used to categorize, cluster, or otherwise group the items into meaningful sets, based on various features associated with the items. Items of each set may be considered likely substitutes for one another. Alternatively or in addition, data mining processes are commonly used to identify items that tend to be viewed, purchased, downloaded, or otherwise selected in combination by users. For instance, items may be identified as likely substitutes for one another if a relatively large number of users viewed the items during the same browsing session. The likely substitutable items identified based on these methods may provide a preliminary basis for recommending alternative items or products to users.